thermal anomalies detection before earthquake using three filters (fourier, wavelet and logarithmic differential filter), a case study of two earthquakes in iran

Earthquake is one of the most destructive natural phenomena which has human and financial losses. the existence of an efficient prediction system and early warning system will be useful for reducing effects of destroying earthquake. in this paper by applying three filters (fourier, wavelet and difference logarithmic filter (ldf)) on soil temperature time-series, anomaly behavior before the major earthquakes was studied. aforementioned methods were performed of the bam (2003), and zarand (2005) earthquakes in iran. the results indicate thermal anomalies were detected before earthquake occurrence. furthermore, the ldf filter detects thermal anomaly as well as the fourier and wavelet filters. for validation of the results, the soil temperature data of the bam earthquake were considered from the bam meteorological station and also from the joroft meteorological stations that located in effective radius (dobrolsky radius) and the same results was obtained. it states that there is a relation between temperature anomaly behavior and the major earthquakes.